Cloud-computing facilities provide computational bandwidth and data-storage services much as utility companies provide electrical power and water to consumers. Cloud computing provides enormous advantages to customers without the devices to purchase, manage, and maintain in-house data centers. Such customers can dynamically add and delete virtual computer systems from their virtual data centers within public clouds in order to track computational-bandwidth and data-storage needs, rather than purchasing sufficient computer systems within a physical data center to handle peak computational-bandwidth and data-storage demands. Moreover, customers can completely avoid the overhead of maintaining and managing physical computer systems, including hiring and periodically retraining information-technology specialists and continuously paying for operating-system and database-management-system upgrades. Furthermore, cloud-computing interfaces allow for easy and straightforward configuration of virtual computing facilities, flexibility in the types of applications and operating systems that can be configured, and other functionalities that are useful even for owners and administrators of private cloud-computing facilities used by a customer.
A typical data center comprises numerous physical and virtual data center objects, such as server computers, virtual machines, virtual data centers switches, routers, and mass data-storage devices interconnected by local-area networks, wide-area networks, and wireless communications. Because of the large numbers of data center objects, information technology (“IT”) administrators rely on data center management tools to collect object indicators. Typical data center management tools calculate current status reports of the data center objects based on the indicators. However, many of these management tools do not provide long-term characterization of the objects. In particular, typical management tools do not project problems with data center objects, cannot determine stability of data center objects over time, and cannot identify which objects experience a degradation in performance over time. Management tools also do not provide a historic summary of data center objects that can be used to determine whether or not object performance problems have been resolved.